Abstract — Automatic Parallel Parking Controller
quality requirements posed by the automatic parking task under real-time perceived local maps, this paper proposes an improved automatic parking planning algorithm based on the A* algorithm, and uses Model Predictive Control (MPC) as the control module for automatic parking. The algorithm enhances the planning real-time performance by optimizing heuristic functions, binary heap optimization, and bidirectional search; it calculates the passability of narrow areas by dynamically loading obstacles and introduces the vehicle’s own volume during planning; it improves trajectory quality by using neighborhood expansion and Bezier curve optimization methods to meet the high trajectory quality requirements of the parking task. After obtaining the output results of the planning algorithm, a loss function is designed according to the characteristics of the automatic parking task under local maps, and the MPC algorithm is used to output control commands to drive the car along the planned trajectory. This paper uses the perception results of real driving environments converted into maps as planning inputs to conduct simulation tests and ablation experiments on the algorithm. Experimental results show that the improved algorithm proposed in this paper can effectively meet the special requirements of automatic parking under local maps and complete the automatic parking planning and control tasks.
Analytical & State-Space Control Methodology
Autonomous driving is currently a hot topic in the automotive industry and has become a key area of intense competition among numerous domestic and international manufacturers and intelligent driving solution providers [ 1 , 2 ] . Once vehicles equipped with advanced autonomous driving become widespread, they will completely overturn people’s travel choices. Tech papers. It can be said that from the government to the private sector, from domestic to international, autonomous driving vehicles have become a core topic in the development of technology and the economy.
Simulink Waveforms & Power Quality Findings
Automatic parking is a very important part of the autonomous driving scenario. The automatic parking system can liberate drivers, save a lot of time and energy, and optimize passengers’ driving experience. Moreover, parking is a part of the driving process with a high incidence of accidents, and the large-scale application of high-performance automatic parking systems can significantly reduce traffic accidents during parking. With the continuous development of automatic parking systems and the further popularization of intelligent cars supporting automatic parking, building unmanned automatic parking lots with small footprints and high efficiency will become a reality from theory.
Scope & Practical Applications
- High-efficiency DC-DC converters and isolated resonant topologies (LLC / DAB)
- Sinusoidal and Space Vector PWM inverters for grid integration & industrial motor drives
- MOSFET / IGBT gate driver optimization with active Miller-clamp shoot-through protection
- Power quality conditioning with Total Harmonic Distortion (THD) strictly compliant with IEEE 519
- Complete Simscape .SLX model files, parameter calculation scripts, and IEEE dissertation reports
Simscape Modeling
Simulink power stage & discrete PWM solver
Semiconductor Loss
SiC MOSFET & IGBT thermal dissipation
SVPWM Control
Vector control, FOC & digital PI loops
IEEE 519 Quality
FFT harmonic spectrum & THD < 5% verification
Gate Driver Protection
Isolated bootstrap & Miller clamp circuits
HIL Prototyping
Ready for dSPACE, OPAL-RT & TI C2000 DSP
Engineering Software & Simulation Toolchains
Modeled using industry-standard power electronics simulation platforms, discrete numerical solvers, and HIL testbeds.
| Software Platform | Analytical Function & Role | Simulation Tier |
|---|---|---|
| MATLAB R2024b | Small-signal state-space averaging, bode stability margins, LC filter design, FFT analysis | Analytical Core |
| Simulink / Simscape | Time-domain switching models, non-linear semiconductor models, discrete PI controllers | System Simulator |
| PLECS / PSIM | High-speed thermal loss estimation (conduction and switching Eon/Eoff), snubber design | Thermal & Losses |
| Altium Designer | High-voltage isolation layout, creepage/clearance, power loop parasitic inductance minimization | Hardware PCB |
| TI C2000 / dSPACE | Embedded C codegen from Simulink, high-resolution ePWM registers, Hardware-in-the-Loop test | HIL Deployment |
Power Conversion & Control Topology Workflow
Systematic integration from DC input energy source and high-frequency gate drive to digital control loops and load delivery.
Renewable Bus
MOSFET/IGBT Bridge
& SVPWM Loop
Filter Stage
& FFT Analyzer
Motor Load
Advantages of the Automatic Parallel Parking Controller Project
Why this project delivers superior academic grades and provides high technical evaluation standing.
High-Fidelity Simscape Modeling
Provides precise numerical simulation of switching events using ODE variable-step solvers without numerical divergence.
Rigorous IEEE 519 Grid Compliance
Guarantees total harmonic distortion (THD) below 5% through optimized LCL filter attenuation and synchronous control loops.
Wide-Bandgap Semiconductor Sizing
Models modern SiC MOSFETs and GaN switches to achieve power conversion efficiencies exceeding 97.5% across full-load regimes.
Advanced Digital Modulation
Implements Space Vector PWM (SVPWM) and sinusoidal modulation maximizing DC-bus utilization by 15.5% over carrier methods.
Dynamic Small-Signal Stability
Custom MATLAB scripts compute control-to-output transfer functions Gvd(s), phase margins (> 50°), and gain margins.
Gate Driver Protection Mechanics
Incorporates active Miller clamps, negative turn-off bias, and isolated bootstrap circuitry to eliminate shoot-through faults.
Hardware-in-the-Loop (HIL) Ready
Directly exportable to embedded C for execution on Texas Instruments C2000 DSPs, dSPACE, and OPAL-RT real-time platforms.
Detailed Magnetic Core Sizing
Features rigorous inductor and high-frequency transformer calculations ensuring core saturation flux margins remain safe.
Direct Electric Vehicle & Grid Value
Builds technical competencies demanded by top automotive EV powertrain developers, solar EPCs, and power electronics consultancies.
Complete Turnkey Package
Delivered with full Simulink .SLX models, MATLAB initialization scripts, calculation sheets, IEEE-format report, and viva defense slides.
Sample MATLAB Code, Scope Waveforms & Harmonic Schedules
Representative excerpts illustrating the state-space analytical derivations, command solver output, and power quality distortion schedules.
[*] Compiling Simscape Electrical Switching Topology Engine... [✓] SiC MOSFET / GaN Switching Semiconductor Characteristics Loaded ──────────────────────────────────────────────────────────────────────── [OUTPUT REGULATION] Steady-State DC Voltage: 24.01 V (Ripple: 0.18 V p-p) [TRANSIENT STEP] 50% to 100% Load Recovery: 0.82 ms (Overshoot: < 1.4%) [SEMICONDUCTOR] Total Switching Loss (Psw): Psw = 4.82 W at 100 kHz [CONVERSION η] Full-Load Power Efficiency: η = 97.42% (Optimal Operating Band) ──────────────────────────────────────────────────────────────────────── [✓] Small-Signal Compensator Verified: Phase Margin = 54.8° (Robust Loop Stability)
[*] Simulating converter steady-state operating envelope across switching cycles...
| Electrical Parameter | Design Objective | Simulink Simulated Metric | Performance Variance | Status |
|---|---|---|---|---|
| Regulated Output Voltage | 24.00 V | 24.01 V | +0.04% | REGULATED |
| Inductor Current Ripple | < 25.0% | 18.4% | -26.4% | OPTIMAL |
| Voltage Peak Ripple | < 240 mV | 180 mV | -25.0% | OPTIMAL |
| Power Conversion Efficiency | > 95.0% | 97.42% | +2.42% | HIGH EFFICIENCY |
[✓] Power Quality Verification Complete: Injected harmonic components conform strictly to IEEE 519 standards.
Frequently Asked Questions
Project Deliverables & Support
Everything needed from project inception to final viva defense — delivered with expert technical support.
.SLX Files
.M Files
Schematics
Report
Slides
Recordings
Sheets
Q&A
Support
Extension